Which integrations are available for this server?

Allows access to Amazon's analyst recommendations and financial performance data through Yahoo Finance. Enables querying of Apple's financial data, stock prices, company profile, leadership information, and market performance metrics through Yahoo Finance. Provides tools for accessing Google's financial information, stock data, and company metrics through the Yahoo Finance platform. Enables comparison of Meta's key financial metrics and valuation measures with other tech companies through Yahoo Finance data. Provides access to Netflix's quarterly income statements and financial performance metrics through Yahoo Finance. Enables symbol search and retrieval of NVIDIA's financial information through Yahoo Finance data. Allows retrieval of Tesla's detailed company information, financial statements, stock performance, and leadership data through Yahoo Finance.

How do I use Zentickr - Yahoo Finance MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Zentickr - Yahoo Finance MCP Server show me Apple's current stock price and analyst recommendations" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Zentickr - Yahoo Finance MCP Server

by chintan-diwakar

Overview Schema Related Servers Score Discussions

Python

Remote

Zentickr — Yahoo Finance MCP Server

Zentickr is a stdio-based Model Context Protocol (MCP) server that gives AI assistants access to 23 Yahoo Finance tools through the yahooquery library—covering prices, fundamentals, statements, analyst research, ownership, events, and symbol discovery.

MIT License Python >=3.10

⚠️ Important Disclaimer

This software is provided for educational and informational purposes only. It does not provide financial, investment, legal, or tax advice. Market data may be delayed, incomplete, or inaccurate. You are solely responsible for your investment decisions; the authors are not liable for any losses or damages arising from use of this software.

Related MCP server: MCP Yahoo Finance

Quickstart

git clone https://github.com/chintan-diwakar/zentickr-yahoo-query-mcp.git
cd zentickr-yahoo-query-mcp
python -m venv .venv && source .venv/bin/activate
pip install -e .

Run the server over stdio:

zentickr

Or:

python -m zentickr

Client setup

Claude Desktop

Add this to claude_desktop_config.json:

{
  "mcpServers": {
    "zentickr": {
      "command": "/absolute/path/to/zentickr-yahoo-query-mcp/.venv/bin/zentickr"
    }
  }
}

Claude Code

claude mcp add zentickr -- /absolute/path/to/zentickr-yahoo-query-mcp/.venv/bin/zentickr

Cursor

Create or update .cursor/mcp.json:

{
  "mcpServers": {
    "zentickr": {
      "command": "/absolute/path/to/zentickr-yahoo-query-mcp/.venv/bin/zentickr"
    }
  }
}

Real-world use cases

Compare Apple and Microsoft fundamentals

Prompt: “Compare Apple and Microsoft fundamentals.”

The assistant can call get_financial_data(symbols="AAPL,MSFT") and get_valuation_measures(symbols="AAPL,MSFT").

Captured output excerpt:

Financial Data:
{
  "AAPL": {
    "currentPrice": 333.26,
    "targetHighPrice": 400.0,
    "targetLowPrice": 215.0,
    "targetMeanPrice": 315.78604,
    "recommendationKey": "buy",
    "numberOfAnalystOpinions": 43,
    "totalCash": 68507000832,
    "totalDebt": 84710998016,
    "totalRevenue": 451442016256,
    "earningsGrowth": 0.218,
    "revenueGrowth": 0.166
  }
}

Valuation Measures:
[
  {
    "symbol": "AAPL",
    "asOfDate": "2026-05-28 00:00:00",
    "periodType": "TTM",
    "ForwardPeRatio": 35.3357,
    "MarketCap": 4589945623560.0,
    "PbRatio": 43.101723,
    "PeRatio": 37.83414,
    "PegRatio": 2.7194
  }
]

Prep me for AAPL earnings

Prompt: “Prep me for AAPL earnings.”

The assistant can call get_calendar_events(symbols="AAPL") and get_earnings_trend(symbols="AAPL").

Captured output excerpts:

Calendar Events:
{
  "AAPL": {
    "earnings": {
      "earningsDate": [
        "2026-07-31 01:30:S"
      ],
      "earningsAverage": 1.89396,
      "earningsLow": 1.83,
      "earningsHigh": 1.99,
      "revenueAverage": 108890141050
    }
  }
}

Earnings Trend:
{
  "AAPL": {
    "trend": [
      {
        "period": "0q",
        "endDate": "2026-06-30",
        "growth": 0.20629999,
        "earningsEstimate": {
          "avg": 1.89396,
          "numberOfAnalysts": 31,
          "yearAgoEps": 1.57
        }
      }
    ]
  }
}

Find NVIDIA's ticker and current price

Prompt: “Find NVIDIA's ticker and current price.”

The assistant can call search_symbols(query="nvidia"), then get_price_data(symbols="NVDA").

Captured output excerpts:

Search Results for 'nvidia':
[
  {
    "symbol": "NVDA",
    "name": "NVIDIA Corporation",
    "type": "EQUITY",
    "exchange": "NMS"
  }
]

Price Data:
{
  "NVDA": {
    "preMarketPrice": 202.155,
    "regularMarketPrice": 207.4,
    "regularMarketDayHigh": 211.08,
    "regularMarketDayLow": 205.85,
    "regularMarketVolume": 116253420,
    "regularMarketPreviousClose": 212.5,
    "exchangeName": "NasdaqGS",
    "marketState": "PRE",
    "symbol": "NVDA"
  }
}

Tool catalog

Market Data

Tool	Arguments	Returns
`get_price_data`	`symbols: str`	Current price and trading data
`get_summary_detail`	`symbols: str`	Day range, volume, dividend, and 52-week range
`get_historical_prices`	`symbols: str`, `period: str \| None = None`, `start_date: str \| None = None`, `end_date: str \| None = None`, `interval: str = "1d"`	Historical OHLCV price data
`get_calendar_events`	`symbols: str`	Upcoming earnings dates and dividend events

Financial Statements

Tool	Arguments	Returns
`get_financial_data`	`symbols: str`	Key financial data, including targets, margins, cash, debt, and growth
`get_balance_sheet`	`symbols: str`, `frequency: str = "annual"`	Balance sheet data
`get_cash_flow`	`symbols: str`, `frequency: str = "annual"`	Cash flow statement
`get_income_statement`	`symbols: str`, `frequency: str = "annual"`	Income statement
`get_valuation_measures`	`symbols: str`	Market cap, P/E, EV, and price/book measures
`get_earnings`	`symbols: str`	Earnings data
`get_earnings_trend`	`symbols: str`	Earnings trend estimates

Analysis & Research

Tool	Arguments	Returns
`get_recommendations`	`symbols: str`	Analyst recommendations
`get_recommendation_trend`	`symbols: str`	Strong buy, buy, hold, sell, and strong sell counts
`get_technical_insights`	`symbols: str`	Technical analysis insights
`get_esg_scores`	`symbols: str`	Environmental, social, and governance scores
`get_company_profile`	`symbols: str`	Company sector, industry, description, and address

Ownership & Governance

Tool	Arguments	Returns
`get_major_holders`	`symbols: str`	Major holders breakdown
`get_institution_ownership`	`symbols: str`	Institutional ownership
`get_insider_holders`	`symbols: str`	Insider holders
`get_insider_transactions`	`symbols: str`	Insider transactions
`get_fund_ownership`	`symbols: str`	Mutual fund and ETF ownership
`get_company_officers`	`symbols: str`	Executives, titles, and compensation

Discovery

Tool	Arguments	Returns
`search_symbols`	`query: str`	Matching stock symbols by company name or partial ticker

symbols is a comma-separated string, such as "AAPL,GOOGL,MSFT". Statement frequency accepts "annual" or "quarterly".

Development

Install development dependencies:

pip install -e ".[dev]"

Run the offline test suite and linter:

pytest
ruff check .

See CONTRIBUTING.md for the full contribution guide.

Data source

Data is sourced from Yahoo Finance through the unofficial yahooquery library. It is subject to Yahoo's terms and no API key is required.

License

MIT — see LICENSE.

Support

Please open a GitHub Issue.

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

1Releases (12mo)

Commit activity

Resources

GitHub Repository

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